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Final Publishable Report
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Project No.: 265954
Project Acronym: ACEM-Rail
Project Full Name: Automated and Cost Effective Maintenance for Railway
FINAL REPORT
Period covered: from 1st December 2010 to 30
th November 2013
Funding Scheme: Collaborative Project
Start date of project: 01/12/2010
Project coordinator name: Dr. NOEMI JIMÉNEZ-REDONDO
Project coordinator organisation name: Centro de Estudios de Materiales y Control de
Obra S.A. (CEMOSA)
Tel: +34 952230842 // +34 651890922
Fax: +34 952231214
E-mail: [email protected]
Project website address: www.acem-rail.eu / www.acem-rail.com
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Table of Contents
1 FINAL PUBLISHABLE SUMMARY REPORT .................................................................... 5
1.1 Executive summary ............................................................................................................ 5
1.2 Summary description of project context and objectives ................................................ 6
1.3 Description of the main S&T results/foreground............................................................ 9
1.3.1 The ACEM-Rail approach and main results ................................................................................ 9
1.3.2 Description of the instrumentation system ................................................................................ 13
1.3.3 Description of main results of the Infrastructure Subsystems Management (ISM) and Decision
Support Tools (DST) allocated in it ........................................................................................................ 26
1.3.4 Description of main results of the Performance Measurement System for impact assessment . 33
1.3.5 Validation of the results ............................................................................................................. 34
1.4 Potential impact, main dissemination activities and exploitation of results ............... 36
1.4.1 Potential impact ......................................................................................................................... 36
1.4.2 ACEM-Rail beneficiaries .......................................................................................................... 38
1.4.3 Main dissemination Activities ................................................................................................... 38
1.4.4 Exploitation activities and achievements ................................................................................... 42
1.4.5 Spin-off companies .................................................................................................................... 45
1.5 Consortium and Contact details ..................................................................................... 46
2 USE AND DISSEMINATION OF FOREGROUND ............................................................ 47
Section A (public) ......................................................................................................................... 47
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1 Final publishable summary report
1.1 Executive summary
Automated and Cost-Effective Maintenance for Railway (ACEM-Rail) is a collaborative research
project funded by the Seventh Framework Programme (FP7) of the European Union. The goal of
the project is to develop the technologies and systems to increase the automation level of railway
infrastructure maintenance and to improve the cost-effectiveness of the maintenance process while
enhancing the quality, the reliability and the competitiveness of railway services.
The project focuses on the track including also track bed, subgrade and engineering structures (such
as bridges, tunnels or retaining walls). It tackles the problem of track maintenance from a
comprehensive perspective including the whole sequence of processes involved in it: since the
monitoring of infrastructure (by means of automated technologies) up to the final execution of
maintenance tasks and going through the evaluation of track condition and analysis of defects’
degradation, optimization of maintenance scheduling (including preventive, predictive and
corrective tasks) and assistance to the operator in field in the execution of maintenance tasks.
All these processes can be structured in three blocks. In all of them, ACEM-Rail has achieved
promising results and has improved the state of the art.
Block 1: Processes oriented towards the automated inspection of the track and evaluation of
its condition. ACEM-Rail has developed six inspection technologies for the automated
inspection of track condition. One of them is based on fibre optic sensors laid along the
track while three of them are embarked on commercial trains. The most promising ones are
those that allow frequent and cost-effective measures (based on fibre optic sensors laid
along the track and embarked on commercial trains).
Block 2: Processes oriented towards the development of a system for the management of the
huge amount of information gathered by the afore mentioned the inspection technologies,
the automation of the maintenance process, the development of Decision Support Tools such
as those for the evaluation of infrastructure condition, the estimation of track degradation
and the optimization and scheduling of maintenance tasks (taking into account
human/technical resources and rail services) and the assistance to the operators in field in
the execution of maintenance tasks and automatic reporting to the office.
Block 3: Evaluation of the sustainability of the maintenance process in terms of economic
impact (cost), social impact (safety and quality of service, user perception and safety
conditions for maintenance crew) and environmental impact (CO2 emissions). A set of
Maintenance Performance Indicators (MPI) is proposed since there is not consensus among
Infrastructure Managers
ACEM-Rail has successfully met all the technical goals in the three blocks above. The results of the
project were validated in the SIEMENS Test and Validation centre in Wegberg-Wildenrath
(Germany), in the railway infrastructure provided by Ferrovie de Gargano (Italy) and in simulated
scenarios based on real railway infrastructure systems. The project has proved to achieve important
benefits in terms of cost, safety, quality and sustainability of railway service. It has also enlarged
the capacity of railway infrastructure.
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1.2 Summary description of project context and objectives
Railway Infrastructure can be broadly structured into: the track, the power supply system and the
signalling/communication. It is a complex infrastructure that requires of a high degree of safety and
reliability. The maintenance of this system is a complicated and expensive task which represent and
important share of total railway infrastructure costs. The maintenance of the track, which decisively
affects both the train safety and passenger comfort, represents around 40% of the total maintenance
cost of the railway system. Therefore, these costs should be kept as low as possible while ensuring,
for a specific train speed, that safety and passenger comfort remain acceptable at all times. An
optimum solution should be sought so as to ensure a satisfactory safety margin and prevent quick
degradation of track quality.
ACEM-Rail is a collaborative Seventh Framework Programme (FP7) project under SST.2010.5.2-1
‘Automated and cost effective railway infrastructure maintenance’, funded by the European
Commission comprising 10 partners from five European countries: CEMOSA (Project Coordinator,
Spain), University of Seville (Scientific Coordinator, Spain), Fraunhofer (Germany), Politecnico di
Torino (Italy), Second University of Naples (Italy), OPTIM-AL (Bulgaria), DMA (Italy),
Tecnomatica (Italy), SIEMENS (Germany) and ScanMaster (Israel). The project duration was 36
months. It started in December 2010. It focuses on track maintenance.
The state of track depends on many factors such as the characteristics and age of the elements, the
track geometry, topography and geology, weather conditions and supporting loads. Furthermore, the
saturation of the capacity of the track sections as a result of increased load of rail services requires
intensified maintenance and the planning and coordination of the rail activities, in order to
accommodate maintenance tasks to the availability of time windows needed to guarantee technical
regulatory levels. Finally, the maintenance management based on cyclical preventive works and on
corrective maintenance entails high costs in both resources reliability and availability of
infrastructure. This situation requires the streamlining of the maintenance management based on
monitoring the track condition, automating the planning management and especially monitoring the
evolution of the parameters that determine the track condition for predictive maintenance and risk
analysis. This schema would allow evolving the traditional maintenance management model based
on corrective/preventive maintenance into a model based on conditions/predictions, helping those
responsible for making decisions to achieve optimal maintenance plans that minimise the
maintenance costs, ensure a satisfactory safety margin and prevent quick degradation of track
quality. This is the goal pursued by the ACEM-Rail project.
ACEM-Rail faces track maintenance from a holistic perspective. It pursues a high degree of
integration of the subsystems affecting the maintenance tasks with the goal of significantly
increasing the automation of track maintenance. The project covers the whole maintenance process
since the monitoring of the infrastructure to the execution of maintenance tasks and the reporting of
the office and including the automation and optimization of the scheduling.
The technologies developed within ACEM-Rail allow maintenance operations to be performed in
an effective way: track inspection will be performed in an unattended and automatic way by
commercial trains (conventional and high speed) and fibre optic sensors laid along the track,
maintenance will be based on condition/prediction, maintenance tasks will be optimally allocated
minimizing track occupancy and maintenance crew will be better assisted and the reporting to the
office will be automated. As a consequence, the cost for maintenance will be reduced and the
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availability of the track will significantly increase. The latter will motivate an increase of freight
transport competitiveness with respect to other means of freight transport such as road.
Besides, because of the better maintained tracks, rail transport will be a safer, more reliable and
more environment friendly mean of transport after ACEM-Rail. Furthermore, the work conditions
for maintenance crew will be safer (better assistance online while the operator is infield and fewer
operations at night time).
ACEM-Rail has also proposed a selection of a suitable set of Maintenance Performance Indicators
(MPIs) to evaluate the economic, social and environmental impact of the proposed maintenance
technologies. This set of MPI was proposed since there is no consensus in MPI’s for Railway
Infrastructure Managers.
ACEM-Rail aims to improve the automation degree of railway maintenance in order to reduce the
cost and improve the safety and quality of rail services. It also improves the safety of maintenance
crew which will work under better and more controlled conditions. To achieve this purpose, the
project has focused on the following goals:
The development of innovative solutions for automated monitoring of railway infrastructure
and for the analysis of infrastructure condition.
The development of algorithms for the evaluation of track degradation taking into account
track condition, rolling –stock characteristics and rail services.
The development of algorithms and tools for an automated planning and scheduling of
maintenance task.
The development of mobile tools to assist the operator in field and to facilitate reporting to
the office.
The development of an intelligent Infrastructure Subsystem Management (ISM) system
which is at the core of the ACEM-Rail concept which integrates and centralizes all the
relevant information (condition, planning and operations) in the same platform and allows
for the automation of maintenance management. Such platform is also the shell to allocate
the Decision Support Tools developed within the project (such as those for optimization of
task scheduling or estimation of track degradation).
The definition of a set of Maintenance Performance Indicators to evaluate and quantify the
economic, social and environmental impact of a better maintenance on rail services.
The above goals have been properly met. As a consequence, the most relevant achievement of the
project can be structured in three fields:
• Development of six inspection technologies for the automated and unattended monitoring of
infrastructure condition. One of them is based on fibre optic laid along the track (which
allows for automatic continuous monitoring). Three on them are embarked on commercial
trains. Therefore, very frequent measures (on a daily basis) are possible (as frequent as rail
services on the trains hosting the instrumentation). This is an important achievement
because no time slot for special testing train is required and the frequent measures allows for
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a close watching on track condition which facilitates the evolution from the classical
preventive /corrective scheme to a more cost effective maintenance policy based on
condition/prediction.
• Development of an intelligent Infrastructure Subsystem Management (ISM) tool which
integrates and manage all data and provides Decision Support Tools (especially those in
charge of the estimation of track degradation and of the optimization of maintenance
scheduling) to help Infrastructure Managers achieve a cost-effective maintenance keeping
the quality and the reliability of rail services.
• Definition of a set of Maintenance Performance Indicators to evaluate the sustainability of
the rail maintenance.
• The demonstration of the technologies developed in real and simulated scenarios.
The expected benefits of the project for the Infrastructure Managers and the Society in general are:
• reduction of cost in maintenance services,
• reduction of impact on rail services,
• increase in safety, quality and reliability of the service,
• improvement in the working conditions of maintenance crews and reduction of work
accidents,
• increase in the capacity of the track and, as a consequence, increase of track availability for
freight transport,
• reduction in CO2 emissions because of more efficient and better organised trips of the
maintenance crew and because of the increase in rail freight transport with respect to road
freight transport.
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1.3 Description of the main S&T results/foreground
1.3.1 The ACEM-Rail approach and main results
ACEM-Rail focuses on the maintenance of the track including the subgrade and structures (track,
track bed and engineering structures such as bridges). It covers the whole process of track
maintenance including the automatic monitoring and inspection of the infrastructure, the analysis of
the track condition and the estimation of defect degradation, the optimization of maintenance tasks,
the generation of work orders and the crew assistance and monitoring of execution of maintenance
tasks and the automatic reporting to the office.
The project has fostered the technologies to facilitate and improve the automation of railway
infrastructure maintenance, including:
The development of inspection technologies for the monitoring of the railway infrastructure.
These technologies included fibre optic laid along the track and structures and inspection
technologies embarked on trains. Among the latter, the most promising are those embarked
on commercial trains. Using the results of fibre optic and of embarked on commercial trains
inspection technologies, allows a very frequency monitoring and supervision of track state
facilitating the implementation of a maintenance policy based on condition/predictions.
The integration and centralization of all relevant information (asset condition, maintenance
planning and operations) in the same platform: Such platform facilitates the automation of
railway maintenance. It is the shell in which some Decision Support Tools have been
allocated.
The main steps (and features) of the ACEM-Rail system are listed below:
1. Monitoring technologies inspect the track and structures. Each technology performs its own
data processing and analysis.
2. All measurements are compiled by a web-based platform for data acquisition, management,
analysis and report (VisioStack).
3. After the different sensor technologies data analysis, a list of defects (and, of course,
location) together with a severity index is automatically generated by the evaluation tools. A
list of warning is also automatically produced.
4. Furthermore, with the help of prediction algorithms, the evolution of the identified defects
taking into account their severity and the characteristics of the traffic and the trains running
on the lines is estimated.
5. The information on identified defects and estimation of evolution is transferred to the
Computerized Maintenance Management System (CMMS) which is the core of The ISM.
6. The CMMS provides all the modules that are required for automated maintenance
management. In ACEM-Rail a commercial solution is adopted (IBM Maximo) on top of
which some especially tailored modules have been developed. One of the most important
modules of the ACEM-Rail ISM is the one devoted for Warning Management and
production of Work Orders.
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7. Warnings are sent to the Maintenance Planning module (ACEM-Rail Optimization tool)
which produces as output a maintenance schedule.
8. The maintenance schedule produced by the optimization tool is converted into Work Orders
in the CMMS. Work orders include detailed instructions of the maintenance tasks to be
performed together with the human and technical resources and timing. Work orders are sent
from the central office to the infield peripheral devices.
9. The maintenance crew infield report to the central office so that the CMMS validates the
execution of maintenance tasks and receives pictures and results of the visual inspection by
the qualified staff.
Moreover, the ISM platform developed within ACEM-Rail generates statistics, reports and
summaries about different factors that may influence the maintenance process and which provide
relevant information for decision makers. Therefore, in the long run, once the system has long
enough data based on historical information, ACEM-Rail will be able to re-evaluate the
convenience of preventive tasks in favour of a condition/prediction based maintenance system.
Figure 1 illustrates the ACEM-Rail concept.
Besides, in order to be able to evaluate the impact of the maintenance procedures and since there is
no consensus regarding Maintenance Performance Indicators within Railway Administrators,
ACEM-Rail also includes the definition of a set of MPIs specially tailored to evaluate the economic,
social and environmental impact of rail maintenance.
The Research and Innovation developments of the ACEM Rail project can be structured in the
following 3 blocks:
- Block 1: Development of innovative technologies for the inspection of the track. Six
technologies were included in the project. Three of them are suitable to be embarked on
commercial trains and have produced promising results: one of them (Laser Profiler and
ISM
MEASUREMENT MANAGEMENT
EVALUATION TOOLS
PREDICTION TOOLS
CMMS PERIPHERAL
DEVICES MAINTENANCE
PLANNING
INSPECTION SYSTEMS
Figure 1. Block diagram showing the ISM modules and external subsystems
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Inertial Pack) is ready for market exploitation while the other two (Hollow Shaft Acoustic
Sensor and Eddy Current and acceleration sensor system) need still some more
developments to be ready for the market. Two of the inspection technologies are only
suitable to be embarked on special testing trains at very low speed and are still far from
market exploitation (Thermographic testing system and Ultrasonic Fuzzy Logic inspection).
Finally, Brillouin Fibre Optic laid along the track and structures was also use to the monitor
the structural health of such assets and train operation. This technology is also close to
market exploitation.
The work developed within Block 1 included also the unique (for all technologies) system to
assign locations to the different measurements (based on odometers) and the use of a web-
based platform to collect all the measurements. Such platform sends the data to the Data
Management System developed within Block 2 below.
- Block 2: Development of an Infrastructure Management System (IMS). This block included
all the work related to the development of an intelligent system able to manage all the data
of the system (including information on the railway infrastructure and its state, rail services
and traffic information, train characteristics, technical equipment and machinery available
and human resources) and the Decision Supports Tools for an optimal performance of the
maintenance systems. Such DST’s comprise those related to the evaluation of defects and
prediction of defect degradation taking into account the severity of the defect and the
characteristics of the traffic and trains and those related to the optimization of maintenance
tasks with a time horizon from one year ahead to the very next future (from next week to 1
or 2 days ahead). Block 2 also includes some mobile tools to support the operator in field for
the execution of maintenance tasks and reporting to the office (including visual inspections).
- Block 3: Evaluation of the impact of the developed maintenance techniques and definition of
a set of Maintenance Performance Indicators to quantify it. In order to analyze the
economic, social and environmental impact and sustainability of the maintenance
technologies developed within ACEM-Rail and since there is no consensus among Railway
Infrastructure Managers, a set of Maintenance Performance Indicators (MPIs) was proposed
and used to quantified the result of the project.
On the other hand, the technologies developed were validated in two demonstrators: the test and
validation centre in Wegberg-Widenrath (Germany, Figure 2) were all the technologies under the
care of SIEMENS (Eddy Current and acceleration sensor system) and FhG – IZFP (hollow-shaft
acoustic sensor and thermographic testing system) were validated.
All the technologies developed but the thermographic and the ultrasonic testing were validated in
Ferrovie de Gargano (Italy, Figure 3) embarked on a commercial train and, in the case of fibre
optic, laid along a stretch of the track and a structure. Thermographic and ultrasonic weren’t tested
in Ferrovie de Gargano because of the technical constraints (low speed).
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Figure 2. Aerial picture and scheme of the demo site 1: The railway test track in Wegberg-Wildenrath
(Germany)
Figure 3 Location and schematic view of the demo site 2: The railway line San Severo- Peschici (Italy)
Figure 4 below illustrates the structure of the project.
Figure 4. Structure of the ACEM-Rail project
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Summarizing, the main results of the ACEM-Rail project are:
1. The development of a set of instrumentation technologies to evaluate track condition
Eddy Current and acceleration sensor system (embarked on commercial trains)
Hollow shaft acoustic sensor (embarked on commercial trains)
Thermographic testing system (embarked on special testing trains)
Laser Profiler and Inertial Pack (embarked on commercial trains)
Fuzzy ultrasonic testing system (embarked on special testing trains)
Brillouin Fiber optics (laid along the track)
2. The development of a comprehensive tool able to compile all the information of the system
and provide the shell to allocate Decision Support Tools to help railway infrastructure
managers. This is a very promising result of the ACEM-Rail which still needs some
development before its exploitation in the market but which it is not very far from it.
3. The development of algorithms and tools able to schedule maintenance tasks in an optimal
and robust to uncertainties way. It is made up of nested optimization algorithms for the
long/medium term (from 2 months to 12 months ahead) and short term (from one week to 2
months ahead).
4. The development of tools based on mobile computers to bring the office to the field and
assist operators in the execution of maintenance tasks.
5. The definition of a set of 24 MPIs to evaluate the economic, social and environmental
impact of the maintenance process.
6. The demonstration of the technologies in two real and simulated scenarios. The real
environments were the Wegberg-Wildenrath Test and Validation Center (Germany), owned
by SIEMENS, and the railway line San Severo – Peschici (Italy), owned by Ferrovie del
Gargano (FdG). Simulated scenarios were developed on top of FdG layout or using some
other railway systems in those cases where the degree of implementation in FdG was not
completed or FdG layout was too simple to prove ACEM-Rail capabilities. In any case, the
suitability and applicability of ACEM-Rail developments to real railway system is
demonstrated.
1.3.2 Description of the instrumentation system
This section describes the main outcomes of Block 1 on the instrumentation technologies.
1.3.2.1 Eddy Current and acceleration sensor system
This inspection system combines two measurement principles: distance sensors based on Eddy
Currents and acceleration sensors. The measurement system combines these two different sensors
channels into a common data set: The distance sensors provide the relative position of the sensor to
the rail while the acceleration data provide the absolute position. The combination of both values
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yields the difference of the actual rail from the ideal line on a length scale of up to several meters
allowing for the evaluation of geometrical defects. Figure 5 below illustrates the basis of the
system.
Additionally, the acceleration data by itself can be used to detect small range defects such as gaps,
dents or corrugation can be detected on a smaller scale in the order of centimeters.
Figure 5 Measurement principle of the Eddy Current system.
As the working distance is about 30 mm by design, the system can be mounted directly to the bogie
of a commercial train. Figure 6 shows the different sensor units for short range and long range rail
contour inspection.
Figure 6 Accelerometer mounted on the wheel bearing (left picture) for short range rail measurement and Eddy
Current sensor + accelerometer (right picture) for long range contour inspection
Figure 7 shows results from the field tests for the Wildenrath test track. Major impacts (blue line)
above the background noise (red and green line for different averaging settings) can easily be
recognized and in some cases could be attributed to infrastructure elements like insulated rail joints.
A visual inspection of the remaining indications revealed several defects of the rail that were
previously unknown to the owner of the test track and were first detected using this method (Figure
8). This was a remarkable result of the validation of this technology in the Wegberg-Wildenrath
Test and Validation Center.
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Figure 7 Wildenrath results along the large test ring obtained at a train speed of 79 km/h. The displayed number
of wheel revolutions corresponds to a track length of 2195.4 m and a duration of 100 s.
Figure 8 Identification and validation of the three main rail indications shown in Figure 7
This technology was also validated in the railway system of Ferrovie de Gargano (Italy). Several
test runs were performed during the last year of the project. By comparing different test runs, also in
different directions of train movement, it could be demonstrated that the obtained indications were
reproducible and, therefore, the instrumentation system was working properly.
The analysis of the measurements in Ferrovie de Gargano also yielded a number of defects in the
tested line between San Severo and Peschici, such as corrugation, flats and joint gaps.
As a summary, it can be concluded that the combined eddy-current and acceleration sensor set-up in
the ACEM-Rail project is very promising because it has been demonstrated its capability to reveal
major rail defects at a possibly minimal equipment cost. Smaller range defects on the order of
centimeters are also directly detectable using only the acceleration data. A comparison with
previous measurements or known infrastructure elements is necessary and also visual inspection
may still be needed to differentiate between different types of defects. However, for rail deviations
over several meters the eddy-current based rail sensor can provide data directly in millimeters
which can be fed into a maintenance concept without need of visual inspection.
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During the field tests the system could be demonstrated up to a speed of 140 km/h due to the
constraints of the test track. Previous experiments on a laboratory set-up showed that the system
could also work for speeds up to 300 km/h.
1.3.2.2 Hollow shaft acoustic sensor
The hollow shaft acoustic sensor system was designed within the ACEM-Rail project for
monitoring both the rail track and the subbase. The system analyses signals produced by the rail-
wheel contact. It includes a combination of acoustic sensors (for high frequency signals detection),
3-D acceleration sensors (for low frequency signals detection) and optionally temperature sensors.
It can be fully integrated in the hollow shaft of a high-speed in-service train (Figure 9 and Figure
10).
Figure 9 Mounting of hollow shaft sensor system
Figure 10 Detailed view of integrated hollow shaft sensor system and software GUI for data acquisition and
evaluation (bottom left).
After the first successful laboratory tests in the facilities of the institute Fraunhofer IZFP-D in
Dresden, the acoustic hollow shaft system was installed and tested at the Siemens test track in
Wegberg-Wildenrath in Germany. The rail car which was used for the field measurements was
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equiped with two hollow shaft systems on a bogie on one side of the rail car (i.e. in series). The
sensor systems in both axles (distance = 2.5 m) were identical so that the data acquisition could be
checked for redundancy and reproducibility, respectively. Furthermore, the continuous position was
recorded via GPS receiver. As the system was only on one of the rails, only that rail was inspected.
In this context, the acoustic sensor system in the hollow shafts worked properly and reliably.
Several individual events along the tracks could be identified: rail joints on straight parts, bends
with and without rim friction, turnouts, etc.
Further field tests were performed at Ferrovie de Gargano along the track between San Severo and
Peschici. In this case, there was one hollow-shaft system in each side of the bogie so that both rails
were inspected. During the measurements several defects could be found along the track (red circles
in Figure 11 top).
Figure 11. Gargano track (top) and field installation of monitoring system (bottom).
The post processing of the data provided by the hollow-shaft acoustic sensors system produces the
following output:
1. Presence of a defect (yes/no)
2. Position of the defect along the rail (by GPS, internal wheel rotation and external odometer)
3. Horizontal dimension of the defect zone (calculated by the duration of the indications)
4. Kind of defect (calculated by HMM (Hidden Markov Models) classification software)
5. Severity index (calculated by the maximum amplitude and the kind of defect)
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The software of this measurement system includes classification routines for data analysis based on
time-frequency representations (spectrograms) of the measured signals which are used as acoustic
fingerprints of the track (Figure 12). Further developments within this technology are required in
the post processing of the data gathered in order to bring it closer to the market.
Figure 12 Spectrograms are used as acoustic fingerprints for the HMM classification software
1.3.2.3 Thermographic testing system
This system is based on the principle of induction thermography. Induced Eddy Currents are
affected by cracks (Figure 13). Increased current densities cause an additional local heating that can
be analyzed by an infrared camera mounted at the train (Figure 14).
Figure 13 Principle of induction thermography
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Figure 14 Position of induction unit and infrared camera at the train
This system was tested at the Siemens test & validation centre in Wegberg-Wildenrath (Germany).
During the measurements, performed along the small inner and the larger outer oval, it was found
that surface cracks are detectable with good signal-to-noise ratio. A detailed analysis showed that
the defect amplitude drops down significantly as a function of train speed v (Figure 15). However
the signal decrease is slower than 1/v. This technology can only be applied for rail defect
identification embarked on special testing trains because of speed constraints. The degree of
development prevented its demonstration in Ferrovie de Gargano (speed constraints).
Figure 15 Defect amplitude as a function of train speed.
1.3.2.4 Laser Profiler and Inertial Pack
Track geometry is probably the fastest deteriorating component of the railways infrastructure.
Moreover, “bad” geometry immediately affects the trains running quality, in terms of safety and
passenger comfort and wheel-rail forces, thus starting a positive amplification loop. This is the
reason why, among the different measurements composing the infrastructure monitoring, the track
geometry has been selected for pushing the automation at the maximum achievable levels.
Automatic measurements can be done frequently. High frequency and accurate measurements are
necessary to compute the deterioration trends that are the base data on which the maintenance
planning can be optimized.
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The inspection technology described in this section is devoted for monitoring the track geometry. It
consists of an inertial pack for creating the reference straight line (or reference curve) and the
optical instruments for giving the deviation of the actual rail shape from the reference one. Figure
16 shows the instrument mounted on a bogie.
Figure 16. Track geometry monitoring instrument mounted on a bogie
The inertial pack consists of 3 gyros and 3 accelerometers (Figure 17). The 3 gyros measure the
rotation on the 3 axis. Integrating the rotations, the attitude angles at any time t are obtained,
relative to a reference position at time t0, when the process is initiated. This way, the direction of the
accelerations and speed vectors are known at any time tn. These directions are fed to the module
integrating the 3 accelerations. The double integration of the accelerations gives the position.
Spatial position and 3 attitude coordinates provide the information needed to place the two rails in
the dimensional space (3D). Thus the inertial pack gives the instrument trajectory in the 3D space
(all 6 degrees of freedom), which is equivalent to having the reference straight line.
Figure 17 Composition of the inertial pack
After having the reference line, the optical instruments measure the distance of the actual rail from
it. The optical instruments are based on the triangulation method, shown in Figure 18.
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Figure 18. Triangulation method based optical instrument
Figure 18 above shows a device measuring just one point. Stacking many of these devices, a whole
profile can be measured (that is, the rails profile is measured). Actually, rather than stacking many
separate devices, a digital camera is used. This can be thought of as a stack of independent line
detectors.
Good algorithms for reading the reflected light improve the measurement accuracy and reduce the
sensitivity to the environmental conditions. Linearization algorithms are necessary as the transfer
function is intrinsically non linear.
This inspection system was successfully proved on the railway line San Severo-Peschici. Figure 19
(left) shows the installation on a passenger coach. The test runs performed along more than a year
allowed to test the accuracy and repeatability of the measurements. Geometric defects such as
gauge deviation, wear or spalling were properly identified. Figure 19 (right) shows an output of the
software used for the data analysis. The differences between two consecutive measurements, red
and blue lines, show the effect of tamping in this particular stretch. This technology is already ready
to be applied in the market.
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Figure 19 On left side, laser profiler and inertial pack mounted in the coach (Ferrovie del Gargano, Italy). On
right side, output of the GUI software. Gauge, cant and curvature in section between KP 65.5 to 66.8. It shows
evident track refurbishments.
1.3.2.5 Ultrasonic testing system
ACEM-Rail included some developments for data processing and defect identification on
measurements provided by ultrasonic inspection system embarked on special testing trains as those
shown in Figure 20.
Figure 20 Slow speed rail inspector for in-service detection and evaluation of flaws.
A typical configuration of an ultrasonic system is shown in Figure 21. It contains various ultrasonic
probes for different kinds of defects and defect orientations.
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Figure 21 Typical configuration of an ultrasonic rail inspection system
Typical results of the ultrasonic inspection system are shown in Figure 22. Several problems
complicate the data evaluation procedure:
Not reliable data – noise, missed indications
Ambiguous defect definition
Slow Reaction time of “conventional” algorithms
Over detection as result of above
Figure 22 Typical results of an ultrasonic rail inspection system
From experience in the field, it is known that trained operators are always able to recognize defects
even within partial and inconsistent data. Therefore, fuzzy logic algorithms promise to provide good
results. They allow minimizing the amount of parameters used for the measurement configuration.
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In the ACEM-Rail project such fuzzy logic algorithms were implemented and tested with already
existing data for defect recognition. . However, this technology wasn’t validated in any of the two
systems (Wildenrath or FdG) used for the validation of the instrumentation techniques. It wasn’t
either validated in the Israeli Railway System as was originally foreseen. Scan Master that was the
partner in charge of this technology used only to validate their algorithms some benchmark data
publicly available from DB.
1.3.2.6 Brillouin Fiber optics
Distributed optical fibre sensors based on Brillouin scattering represent a promising technology to
monitor the structural integrity of the rail tracks, as they allow a spatially-continuous monitoring
over distances that can reach tens of kilometers with the spatial resolution of one meter.
The main advantage of this technique is that a single optical fibre can be used as a sensor over
distances of tens of kilometers. Hence, the distributed fibre sensor can contribute significantly to
increasing rail safety, permitting to quickly identify anomalies or interruptions of the rail tracks
A portable Brillouin optical time-domain analysis (BOTDA) measurement central unit was
developed in ACEM-Rail project, to be employed for structural health monitoring of railway
infrastructures. A sketch of the newly realized BOTDA central unit is shown in Figure 23 (left),
while Figure 23 (right) shows a photograph of the prototype.
Figure 23 On the left side, sketch of the optoelectronic unit. On the right side, picture of the realized prototype
The whole acquisition process is fully automated. The measurement takes place by running a
MATLAB® script, by which it is also possible to set the measurement parameters. Another
MATLAB® script processes the acquired data, thus providing the temperature or strain profile
along the sensing fibre.
After laboratory tests, the fiber optic inspection system was placed in a rail bridge of the San
Severo-Peschici line (Figure 24). This 3m-long stone bridge presented some cracks near the
keystone in the seaside. It was detected an abnormal dynamic behaviour of the bridge close to this
cracks during the passing of trains.
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Figure 24 Rail bridge at San Severo-Peschici railway line, near San Menaio Station. It shows cracks at the
seaside keystone of the bridge.
Moreover, as well as the above developments for infrastructure monitoring, this technology was
also used for train monitoring. This wasn’t originally planned for the project but was found to be an
extra development which enriches the system. In this case, a standard single-mode optical fiber was
attached along a 60m-long rail by using an epoxy-based adhesive (Figure 25). The optical fiber was
protected by a tight-buffer PVC jacket with a diameter of 900 μm. The fibre was deployed as a loop
with the return path not bonded to the rail and employed for measuring the temperature in proximity
of the rail.
Figure 25. Fiber optic sensor glued to the rail foot at the railway line San Severo-Peschici (Italy)
The measurements were made in different dates, allowing assessing the influence of different
factors such as temperature and humidity, as well as performing useful measurements for train
operation. Measuring axel loads (static and dynamic), axles number and distance (identification of
the train), direction and train speed (constant or accelerating) was possible using this method.
Figure shows the output of a dynamic strain acquisition during a train passage.
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Figure 26. Distributed dynamic strain acquisition during train passage. The 12-axles diagnostic train is
acceleration along the monitored section.
1.3.3 Description of main results of the Infrastructure Subsystems Management (ISM) and
Decision Support Tools (DST) allocated in it
At the core of the ACEM-Rail approach there is a comprehensive system that organize and manage
all the relevant information and provides the shell to allocate several decision support tools to assist
infrastructure managers. Some of these Decision Support Tool have been developed in an external
module that communicates with the core of the ISM system (such as those for the optimization of
the planning and scheduling of maintenance tasks) while others were directly developed into the
ISM system (such as those for warning management or work orders generation).
1.3.3.1 General description of the ISM
The Infrastructure Subsystems Management (ISM) manages and integrates all relevant information
and tools that are required for the automation, control, monitoring, planning, optimizing and
tracking the maintenance management process. The ISM is also the channel through which
information is communicated from one to another ACEM-Rail system, making the whole project
working in a coherent and coordinated manner, as shown in Figure 27. It has been implemented
over a commercial tool (IBM MAXIMO Spatial and Linear Assets).
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Figure 27. Integration of the ISM with other subsystems of ACEM-Rail
The Warning Management module developed into the ISM is the basis for the maintenance
automation system developed in ACEM-Rail. This module makes use of some of the advance
features already included in IBM MAXIMO together with additional logic specially tailored in
ACEM-Rail.
Warnings correspond with defects, degradations or abnormal conditions of the infrastructure that
require control, monitoring and eventually correction. This ISM’s Warnings management module
manages the life cycle of the warning from the entry point (notification of a new defect) to the end
point (the warning is cancelled or the defect is corrected). There are two main phases on the
warning management workflow:
1. Analysis & planning phase: In this phase, warnings are managed automatically to determine
when and how a maintenance action has to be performed.
2. Work order phase: In this phase, the warning is converted into a work order or a set of work
orders. Work orders are scheduled and assigned to specific time slots and maintenance crew.
Once the work order is accomplished, the system receives feedback form the crew about the
execution procedure and the state of the infrastructure.
Figure 28 shows the life of a warning. Blue colored cells correspond to the processes in Phase 1,
while orange ones correspond to Phase 2 processes.
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Figure 28. Warning management workflow
Phase 1 starts with the warning generation. A warning can be generated after:
Evaluation Tools: as a result of the analysis of the measurements.
Visual inspections/maintenance executions: during in field operations while performing
maintenance operations (including visual inspections).
Preventive maintenance master plan.
After a preliminary validation of incoming warnings, the system determines whether a warning
corresponds to a new defect/warning or to a previous reported warning. For previous warnings, the
process estimates the current state of the defect as a function of the reliability of the sensor and the
acquisition date. Depending on the reliability of data and the associated risk, the process can select
different workflow paths: i) visual inspection for poor reliability; ii) tactical planning loop for high
confidence and low risk; or iii) corrective maintenance for high reliability and high risk.
One of the main tasks developed within Phase 2 is the integration and communication with the
systems and tools based on mobile systems for the in-field execution and monitoring of
maintenance works.
1.3.3.2 Optimization
Mathematical optimisation of maintenance planning plays a crucial role and fills a gap existing in
classical railway maintenance approaches which schedule maintenance tasks using only experience
and some simple rule based algorithms. The final goal behind ACEM-Rail is to achieve the (partial)
automation of the overall maintenance process. ACEM-Rail system performs very frequent
measures of the infrastructure state. Huge amount of previously unavailable data will be collected
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and pre-processed by sensor systems for automated inspection. This information will be stored and
manage to improve the maintenance of the infrastructure.
In order to optimally make use of this information, software tools for maintenance planning are
indispensable, and the optimisation of resource allocation, scheduling of tasks and on similar
objectives will be enabled. Only with this step the full benefit of automatizing the maintenance
process will take effect.
Within the ACEM-Rail project, solutions for two different levels of maintenance planning (tactical
and operational) have been developed. They are consecutive and have to be coordinated in practice:
the tactical and the operational planning.
The tactical planning focuses on a medium term time horizon (1 year). It is based on predictive
information. It is in charge of the selection and temporal allocation of warnings into time slots. The
resulting selected jobs (warnings) together with their track position (time slots) for the short-term
(next few days or weeks) are the input for the 2nd
optimization tool which is the operational
planning.
Within the operational planning, a detailed scheduling of human and technical resources is
performed in order to perform the maintenance jobs. The operational planning is based on real-time
data (execution time, availability, etc).
Figure 29 below shows the relationship between tactical and operational planning and very short
term work order plan sent to the maintenance crew.
Figure 29. Optimization
For the tactical planning, it has been shown that it is important to take into consideration the
probabilistic information derived from historical maintenance data and degradation models for
infrastructure elements. By doing so, it is possible to estimate the future degradation process as well
as the costs incurred by future maintenance interventions. This enables operators and dispatchers to
make decisions on scheduling of maintenance operations based on well-founded calculations.
As a solution methodology for tactical planning it is proposed the Monte-Carlo Rollout method,
which has been modified and adapted within ACEM-Rail to the specific characterisations of the
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stochastic optimisation problem at hand. The comprehensive computational experiments made
using real-world data can be concluded as follows:
- The improvement in the feasibility of maintenance schedules is the main advantage of the
Monte-Carlo Rollout method. The occurrence of all three kinds of infeasibilities (due to safety
restrictions, track possession booking, and resource availability) could be reduced drastically by
looking at future scenarios.
- The evolution of cost values in future scenarios is very robust against uncertain developments.
Other than using classical deterministic approaches, where costs are dealt as constant e.g. by
using expected values, the Monte-Carlo Rollout method is able to estimate future increases in
costs and to provide schedules that select warnings according to a robustness criterion.
Considering the operational planning level, the investigations carried out in ACEM-Rail have
shown that there exists a very high diversity in planning processes and tasks applied to different
railway companies and maintenance operators. Due to this fact, it is not possible to design a general
model of an operational planning problem, as it is the case for the tactical planning. Rather the
developments have focused on specific sub-tasks that have high influences on overall costs and
resource consumption, where the planning of maintenance tasks is a complex procedure and the use
of optimisation tools can have a significant effect.
An example for such a sub-task is the problem of ballast tamping for a rail network system. Within
ACEM-Rail it has been demonstrated the solvability of such a complex planning task using an
appropriate optimisation model and implementing an efficient local search procedure (Simulated
Annealing). The results showed a high potential for cost reductions to be achieved in comparison
with traditional planning and optimisation methods.
The modelling was made in such a way that the developed ICT tool is easily adoptable to similar
tasks in operational planning. Therefore, despite focusing on the ballast tamping problem the
planning tools have demonstrated their usefulness based on mathematical optimisation for a whole
class of operational planning problems.
The demonstration of the optimisation tools was based on simulated scenarios due to the incomplete
implementation of the ISM in the Ferrovie de Gargano’s organisational structure and the
unavailability of historical data for feeding the optimisation algorithms.
The tactical planning tool was tested on a benchmark consisting of real infrastructure data from the
real line San Severo-Peschici extended with complementary information from other Infrastructure
Managers, such as maintenance procedures, performance and strategies, which were adapted to the
features of the FdG’s facilites. A list of simulated warnings on this real infrastructure was the input
for the optimisation algorithms.
On the other hand, the operational planning tool required a more complex infrastructure network for
demonstration. In this case, the simulated scenario consisted of a multimode network where the
track condition for each stretch was chosen at random. Figure 30 shows the simulated railway
network with indication of the daily costs for traffic interruption at each stretch.
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Figure 30 Cost map. Simulated scenario for demonstration of operational planning tool
The results showed the applicability of a complex planning task using appropriate optimization
models It can be concluded a high potential for cost reductions to be achieved by the proposed
optimization methods in comparison with the traditional planning tools and systems.
1.3.3.3 Prediction tools
ACEM-Rail includes not only the development of tools to evaluate the track condition but also
those to estimate the defect evolution taking into account a number of aspect such as the type and
severity of the defect, the layout and characteristics of the stretch (such as straight, curve, slope, etc)
where the defect is, the traffic (frequency of the trips) and the features of the train running on the
track (load, speed, acceleration, …).
In order to evaluate the track condition, different aspects must be considered (geometry, profile
conditions, ballast, subgrade, vehicle behaviour, etc). These aspects have been aggregated in a
certain number of scalar “Quality Parameters (QP)” chosen in order to allow:
1. calculating the QP from the measures;
2. and estimating the evolution of the QP on the basis of statistical/physical considerations.
Moreover, the selected QP do not mismatch the safety/availability criteria defined by the recently
developed EU TSI.
The track condition evolution depends on the factors mentioned above (defects and their severity
index, type of stretch, traffic and train characteristics, etc). In order to evaluate the track condition,
it is divided into stretches with uniform track types. QP’s are calculated for the different stretches
making up the line under consideration
QP’s, which are linked to certain locations or stretches, can be used to identify defects types and to
assign a severity index (as defect and quality indexes are complementary to one another). Defects
on a track can be generally divided into those related to the geometry of the track (such as gauge
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deviation, track twist or incorrect curve radius) and those linked to the mechanical efforts (such as
cracking, shelling, or crushings).
In order to estimate the evolution of the QP’s (or conversely, the evolution of the defects), two
methodologies have been used:
1. The evolution of the QPs dealing with geometric defects was performed using multibody
simulations to consider the effect of an specific number and type of trains running on the
track.
2. The evolution of the QPs dealing with mechanical defects was carried out using theoretical
degradation laws (exponential, potential, logarithmics or linear paths) which only depend on
the cumulated gross tones and not on the vehicle-track interaction forces. A more
sophisticated evolution of mechanical defects including wheel/rail interaction is a further
line of development of the project.
Both, the information on the type and severity index of the defect and the information on the defect
degradation or evolution is sent to the ISM (CMMS) in order to generate the warnings required by
the optimization algorithms developed in the project.
1.3.3.4 Mobile tools to assist maintenance crew in field.
ACEM-Rail includes some tools to assist the operator in field. The maintenance crew receives the
list of maintenance tasks using these mobile tools. Maintenance tasks are converted into a pack of
simple but detailed work orders which includes all the steps, work plan, itinerary, technical
information and resources necessary to perform the repair in an optimal way. These work orders
reside in a “Maintenance Master” application, which is an external tool of the ISM with two
versions: one for the central office (office application in Figure 31 below) and another one for crew
mobile devices (mobile application in Figure 31 below).
The office application is used by the maintenance manager and its main function is to assign
the work orders to specific maintenance teams and to monitor the progress of the execution
of works.
The mobile application is synchronized with the office application. Using of theses mobile
devices, the field operator can read in-situ the work instructions and report the progress of
work. On the other hand, operators can report to the office and send the results of visual inspection using
the same mobile tools.
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These mobile applications were validated in the line San Severo-Peschici (Italy) in the railway
system of Ferrovie de Gargano. Two field tests were performed dealing with the inspection
activities in track and structures defined as part of the preventive maintenance in Ferrovie de
Gargano. Several aspects were successfully proved, such as the data transmission via wireless, the
capturing of pictures, the in-field measuring and the reporting to the office.
1.3.4 Description of main results of the Performance Measurement System for impact
assessment
In order to measure the effectiveness and efficiency of ACEM-Rail system in a quantitative way, a
set of 24 Maintenance Performance Indicators (MPIs) was defined. These indicators were classified
in an architecture similar to the one proposed in the standard UNE-EN 15341:2007 (CEN, 2007).
This standard distinguishes among three types of indicators (economical, technical and operational)
within three levels (company, system and unit). Within ACEM-Rail, a similar MPI’s matrix
structure which has added two extra groups (on social and environmental issues) was developed.
Figure 32 below presents ACEM-Rail MPI’s. The detailed definition of each MPI (e.g. MPIE1 can
be found in the public deliverable D8.1 which can be downloaded from the project website).
Figure 31. The Maintenance Master consists of an office application and a mobile
application, both synchronized and communicated via wireless or USB.
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Indicator Level
Level 1
Company
Level
Level 2
System
Level
Level 3
Unit Level
Indic
ator
Gro
up
Economical
indicators MPIE1
MPIE2 ,
MPIE3
MPIE4,
MPIE5
Operational
indicators MPIO1
MPIO2 ,
MPIO3
MPIO4,
MPIO5
Technical
indicators MPIT1 MPIT2
MPIT3,
MPIT4,
MPIT5
Social
indicators MPIS1
MPIS2 ,
MPIS3 MPIS4
Environmental
indicators MPIN1 MPIN2
MPIN3,
MPIN4,
MPIN5 Figure 32. Architecture of Maintenance Performance Indicators used in ACEM-Rail
The Performance Measurement System developed constructed upon these MPIs has shown its
suitability for assessing the improvements achieved in the whole railway system by the
implementation of the ACEM-Rail developments. ACEM-Rail project included an estimation of the
economic, social and environmental benefits that were expected at the end of the project. This
estimation was made before the project started. After the final evaluation of the ACEM-Rail
performance, the following conclusions were achieved:
The economic, organizational and technical impacts are similar to the expected ones,
according to the ACEM-Rail objectives.
The social benefits could not be assessed because of the partial implementation in FdG,
nevertheless this impact is considered small in this context due to the limited influence
of track quality in customers’ satisfaction in Gargano.
The environmental impact –reduction of CO2 emissions- is higher than expected due to
the enormous savings in travel distance by maintenance crew enabled by the better
scheduling of maintenance tasks and organization of trips and the removal of the paper-
based workflow.
1.3.5 Validation of the results
As already mentioned in Section 1.3.2, three inspection technologies were validated at the
Wegberg-Wildenrath test and validation centre (Germany), owned by SIEMENS in July 2012:
Eddy Current and acceleration sensors
Non-contact thermographic testing system
Hollow-shaft acoustic sensor
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On the other hand, all the technologies embarked on commercial train together with the fibre optic
system were validated in a real railway infrastructure, the line San Severo-Peschici, located in
Puglia (Italy) and owned by Ferrovie de Gargano (FdG). This validation included several tests/runs
that were time separated within the period in between January 2012 and September 2013. The
technologies validated in FdG are listed below:
Laser profiler and Inertial pack
Eddy Current and acceleration sensor
Hollow-shaft acoustic sensor
Fiber optic sensors
Regarding the validation of the mobile tools for aiding and monitoring the execution of
maintenance tasks, as already mentioned in Section 1.3.3.4, they were successfully demonstrated at
the line San Severo-Peschici on June 2013, by inspecting both track and structures.
On the other hand, the Infrastructure Subsystems Management and the ICT decision support tools
for optimal maintenance planning described in described in 1.3.3 were tested on simulated scenarios
due to the incomplete implementation of the system in the Ferrovie de Gargano’s organizational
structure, on the one hand, and the simplicity of the line San Severo-Peschici for proving the
benefits of some of the optimization algorithms (those for operational planning), on the other hand.
These scenarios were constructed upon infrastructure data from FdG and other Infrastructure
Managers. Therefore the feasibility of application to a real railway environment was also proved.
Finally, the economic, social and environmental impact of ACEM-Rail was also assessed for FdG
environment using the ACEM-Rail’s MPI’s system consisting on 24 indicators.
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1.4 Potential impact, main dissemination activities and exploitation of results
In this chapter the project impact is summarized, followed by all dissemination and exploitation
activities and achievements.
1.4.1 Potential impact
One of the main features of the ACEM-Rail approach is that it tackles the problem of track
maintenance in a comprehensive way covering the different stages and agents involved. Therefore,
as a whole, the ACEM-Rail project will mean an important step forward in the state of the art of
railway maintenance.
ACEM-Rail has achieved some progress beyond the state of the art in the following fields:
1. Progress beyond the state of the art has been achieved in relation to automated and
unattended track monitoring embarked on commercial trains (conventional/high speed and
passengers/freight). This allows very frequent measures of track state and therefore very
accurate knowledge on track condition and degradation estimation. Besides, ACEM-Rail has
also produced some advances in the use fibre optic technologies for monitoring the state of
the track and the operation of rail services. All of this will allow evolving from classical
railway maintenance policies based on predictive/corrective maintenance to a more cost-
effective and reliable maintenance based on conditions/predictions. On the other hand, the
instrumentation system proposed will generate a large amount of data that will have to be
efficiently managed and structured. For that reason item 2 below is developed.
2. Progress beyond the state of the art has been achieved in relation to asset management
systems for linear infrastructures and, in particular, for railway. ACEM-Rail has developed
an Infrastructure Subsystem Management (ISM) system which manages and centralizes all
the information on the railway system in the same platform and allows for the
communication and interaction of the different modules of the ACEM-Rail approach. The
ISM system is the tool that allows automating the maintenance process. It also provides the
shell to allocate Decision Support Tools to help Railway Infrastructure Managers. This tool
was developed on top of a commercial tool (IBM MAXIMO). Its development was modular
to facilitate its gradual application in a real railway system.
3. A Performance Measurement System is proposed to evaluate the economic, social and
environmental impact of the maintenance process and, in particular, of the ACEM-Rail
system
4. Besides, the achievement shown in item 2 above in relation to maintenance of railway
systems can be very easily transferred to the management of other linear infrastructures such
as roads. Therefore the Infrastructure Subsystem Management (ISM) system developed
within ACEM-Rail also is also step forward for the management, automation and
optimization of road maintenance.
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The combination of items 1 and 2 above allows an important modernization and automation of the
railway maintenance which will allow for:
An important reduction in the cost because of the more efficient use of human/technical
resources and because of a longer life of the track due to the fact that it will be better
maintained (closer monitoring and more efficient management). The reduction of the costs
of maintenance operations will be due to the automated inspection techniques embarked on
commercial train to automatically inspect the track (the expensive measurement trains, used
today, will not be required), to the intelligent maintenance tools developed to optimize and
automate the process (reducing time and resources) and to the longer life of the track
because of the better maintenance of the track.
An improvement in the safety of rail services because of the better condition of the track
and a reduction in maintenance crew working accidents because of the better and more
assisted working condition of the maintenance crew.
An improvement of the quality of rail services due the better comfort conditions (because
of the better quality of the track) and the fewer disruptions of rail services (because of better
maintenance tracks and more robust to uncertainties planning of maintenance tasks) and
also an improvement on the reliability of the system due to same reasons.
A reduction in the number of trips of the maintenance crew and as a consequence a
reduction in CO2 emissions in these trips due to the reduction of paper work because of
the mobile tools developed and the better planned trips because of the optimization
algorithms.
Finally, the capacity of the track will be enlarged because of the better management of
time slots for maintenance tasks. On the one hand, the time slots for special inspection
trains will not be required as the track would be inspected at the same time that rail services
are provided. On the other hand, the planning of maintenance tasks is optimized and is
more robust to uncertainties and, as a consequence, the less maintenance time slots are
required. Besides, the better assistance to operator in field also reduces the time for the
execution of maintenance tasks. The addition of all these factors allow for an enlargement
of time slots for rail services which will produce an increase in rail freight services.
Hence, less CO2 emissions and other pollutants will be expelled because of the market
share transferred from freight road transport to freight rail transport (being rail transport
greener than road one.
Thus, the ACEM-Rail Project has achieved important benefits, both socio-economic and
environmental. In summary, the Project has increased the cost-effectiveness and the automation
degree of railway infrastructure maintenance. All of this helps to improve the competitiveness of
European rail transport significantly reducing inspection and maintenance costs and increasing the
safety, quality and reliability of rail services. Moreover, all of this also contributes to the reduction
of pollutants expelled to the atmosphere for a greener and more sustainable European transport
system.
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1.4.2 ACEM-Rail beneficiaries
One of the most important aspects to consider in any research project is to identify potential stakeholders or
main beneficiaries of the technology developed in the project.
The main stakeholders/beneficiaries/customers of the products and results developed in the ACEM-Rail
project are:
Railway authorities and operators
Transport planners and engineers
Rail maintenance and repair services companies
Railway infrastructure planners and designers
End-users of rail services
1.4.3 Main dissemination Activities
During the three years of the project, the ACEM-Rail partners were highly active in disseminating
the project’s results in high-quality conferences and journals, liaising with related research projects,
making promotional material, among other activities. 19 scientific papers have been prepared,
submitted, accepted for publication, and presented in conferences. Besides, 49 dissemination
activities have been conducted, including industrial workshops attended and fairs. The project’s
main dissemination activities are organized below in 3 categories: publications, workshops and,
other activities.
1.4.3.1 Publications and Scientific Conferences
During the project numerous publications were written such as press releases, a project website,
scientific contributions to scientific journals and conferences as well as scientific theses carried out
by students.
Publications at conferences and journal papers have been one of the major instruments to
disseminate ACEM-Rail research results to the scientific community. This guarantees, on the one
hand, that the research of ACEM-Rail goes beyond the current state of the art and facilitates, on the
other hand, the possibility that the research can be carried on even after the project’s completion.
The dissemination activities covered a set of different events, including the following scientific
conferences:
IEEE Sensors Conference
World Congress on Railway Research (WCRR)
International Conference on Railway Technology: Research, Development and Maintenance
(RAILWAYS)
Transport Research Arena (TRA)
International Conference on Road and Rail Infrastructure (CETRA)
International Conference on Operations Research and Enterprise Systems (ICORES)
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European Workshop on Optical Fiber Sensors (EWOFS)
International Conference on Stochastic Programming (ISCP)
International Conference on Soft Computing Technology in Civil, Structural and
Environmental Engineering (CSC)
Euro Working Group on Transportation (EWGT)
European Transport Conference (ETC)
Pan-American Conference of Traffic and Transportation Engineering and Logistics
(PANAM)
Spanish Conference on Railway Innovation
Transport Engineering Conference (CIT)
The list of project publications is given in the Tables A1 (peer-reviewed publications) and Table A2
(dissemination activities).
1.4.3.2 Workshops, Exhibitions and Scientific Theses
Some partners have attended to exhibitions or have organized technical meetings/workshop with
national authorities (see Table A2).
Moreover, the project consortium organized a Public Final Workshop, which was held during the
European Transport Conference (ETC2013), in a special double-session:
Open ACEM-Rail Final Workshop on ‘Towards a More Efficient and Sustainable Railway
Maintenance’ in Frankfurt (Germany), on 30 September 2013. Presentations and papers
from ACEM-Rail members were given.
On the other hand, the PhD Thesis ‘Generalized Bin Packing Problems’ has been completed at
Politecnico di Torino (POLITO) in 2013. In this regard, some ACEM-Rail results are currently in
use in lecturing in specialized Railway course.
1.4.3.3 Other dissemination activities
The ACEM-Rail Team has produced promotional materials, as website, posters, flyers and
newsletters.
The logo (Figure 33) was designed at the initial stage of the project and was used in the documents
produced during the project (brochure, presentations, newsletters, deliverables, etc…), both internal
and external ones.
Figure 33: ACEM-Rail Logo.
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The ACEM-Rail project generated two brochures (Figure 34 and Figure 35):
- One of them at the beginning of the Project with general information on the project and
information interesting for prospective users.
Figure 34: First version of the ACEM-Rail Brochure.
- Another brochure was produced at the end of the Project. This flyer is focused on the key
achievements and on the demonstration pilots.
Figure 35: Brochure for the Final Project Workshop.
Other dissemination materials were the Posters (Figure 36). An initial poster was produced and
used on exhibition booths of Partners within some events, as EXPO Ferroviaria 2012 or
Defektoskopie 2011. Moreover, another poster was also produced and displayed in the Final
ACEM-Rail Project Workshop as publicity material.
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(a) (b)
Figure 36: ACEM-Rail Posters, (a) ACEM-Rail Poster showed at EXPO Ferroviaria 2012 and (b) ACEM-Rail
Poster for the Final Project Workshop.
On the other hand, three informative newsletters (Figure 37, Figure 38 and Figure 39) have been
produced and published (at the 9th, 18th and 30th month); including interviews (to Partners and
former Project Officer), key achievements reached, work status and news of upcoming events. Each
Newsletter was adjusted to current project state and described selected issues related to the project’s
development.
The following Figures show all published newsletters.
Figure 37: Pages of the first issue of ACEM-Rail Newsletter.
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Figure 38: Pages of the second issue of ACEM-Rail Newsletter
Figure 39: Pages of the third issue of ACEM-Rail Newsletter
1.4.4 Exploitation activities and achievements
This section focuses on foreseen exploitation of project results. A general description is provided
here.
ACEM-Rail has produced interesting outcomes which can be exploited in the field of
instrumentation technologies (Block 1 in Section 1.3.1) and in the field of Infrastructure Subsystem
Management and Decision Support Tools (Block 2 in in Section 1.3.1). In most cases, some more
research and development activities are necessary to be able to meet market demands at a
reasonable price. In other cases, there are results that can be exploited in the very short term.
Regarding instrumentation technologies a brief summary of main possible foreseen exploitation is
presented below:
The most mature technology developed within ACEM-Rail for track inspection is the
technology developed by DMA based on laser profiler and inertial pack. DMA is going to
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offer the unattended monitoring capability for every track inspection car they produce, be it
required or not, because it eliminate the operator errors in the defect localization. This
technology is ready for market exploitation.
The inspection technology based on the hollow shaft acoustic sensor developed by
Fraunhofer- IZFP-D needs some more developments mainly in the field of data post
processing and automated defect recognition. The partner Fraunhofer-IZFP hasn’t foreseen
any exploitation at this stage.
The technology developed by SIEMENS based on Eddy Current performs very well when
the track is in a good condition and the probe can be closer to the rail. For poor maintained
tracks that present more geometry defects, the probe cannot be that much close to the rail
(because it can crash with it) and the signal is noisier and produces worse results. The
accelerometer sensor system also has some problems when locating the exact position of
the rails. A possible collaboration between SIEMENS and DMA was mentioned during the
last meeting of the project in order to avoid these positioning problems. SIEMENS foresees
exploitation of their results in three products as shown in Table B2 (confidential).
The technology on stimulated Brillouin scattering in optical fibre developed by SUN has
shown promising results in retrieving information for structural heath monitoring of railway
infrastructure and to retrieve information about the rail traffic. Further research is required
to improve both the spatial resolution and the acquisition rate of the proposed sensors. In
any case, at this stage, it is foreseen the commercial exploitation of Interrogation unit for
distributed strain and temperature measurements.
The algorithms developed by Scan Master for the processing of the data provided by the
ultrasonic railway inspection systems can also be commercially exploited.
Regarding the Infrastructure Subsystem Management (ISM) and Decision Support Tool, the
following results are subject to commercial exploitation, after some more research and
development activities:
The ISM is a very promising tool that will significantly improve the effectiveness of the
maintenance process not only in railways but in general in linear infrastructures. To get the
system closer to the market for a commercial application, the communications and
interfaces of the ISM with the optimization algorithms and the mobile tools have to be
automated. A collaboration of some partners of the ACEM-Rail (CEMOSA, US,
Fraunhofer IVI and DMA) is foreseen for this commercial exploitation.
Software tools for long-term tactical infrastructure maintenance planning and short-term
operational infrastructure maintenance planning can be subject to commercial exploitation
by Fraunhofer IVI.
The mobile tools to help the operator infield and monitor the execution of maintenance tasks
are subject to be commercially exploited by OPTIM-AL.
On the other hand, ACEM-Rail project has also produced an important general advance of
knowledge to most of the partners. In particular:
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CEMOSA has advanced its knowledge and expertise in the following fields: requirements,
characteristics and capabilities of sensors technologies for rail monitoring; analysis of
maintenance procedures for railway (technical requirements, costs and resources), RAMS
and LCC railway infrastructure design and asset management and logistic planning of
maintenance operations. CEMOSA is now in a better position to offer more added value to
its customers in the railway sector. In particular, CEMOSA is in a better position to provide
the following new or improved services:
o Technical assistance to Infrastructure Managers for the sensor selection and design
of the monitoring system for the inspection of the track/pavement, the subgrade and
structures. Data analysis and evaluation of the infrastructure condition. Estimation of
defect degradation.
o Technical assistance to Infrastructure Managers for the implementation of an ISM
system, including organisational changes, sequential implementation and evaluation
framework
o Technical assistance to Infrastructure Managers for optimized RAMS and LCC
oriented management of railway maintenance system.
o RAMS and LCC oriented design for new and upgraded railway infrastructures
US has advanced its knowledge in the field of asset management and logistic planning of
maintenance operations.
SIEMENS has advanced its knowledge in the implementation of common techniques for
vehicles inspection (Eddy Current, accelerometers) to infrastructure monitoring. The
automation level of this system (i.e. power on, measurement and power off without human
intervention) is also a new achievement for this company.
DMA has advanced its knowledge in the improved accuracy of the profiler, which enables
de detection of a wider range of track defects, as well as the web-based management of
acquired data.
FhG-IZFP has advanced its knowledge in the field of railway inspection. The used sensor,
hollow-shaft acoustic sensor and Thermographic, have been widely applied to wheel
monitoring, but this project is the first approach to infrastructure monitoring.
FhG-IVI has advanced its knowledge in the field of maintenance planning. The new
developed algorithms have demonstrated to be more cost-effective than current optimisation
techniques and they can be applied to any linear infrastructure.
SUN has advanced in its knowledge in the field of railway inspection. The Brillouin fiber
optic sensor have been widely used in the monitoring of engineering structures, such as
bridges, but few experiences exist dealing with the monitoring of train services because of
the technical difficulties with the dynamic acquisition of data. The new interrogation unit
allows exploring this new application.
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SM has advanced in its knowledge in the interpretation of raw data from ultrasonic
inspection by the application of Fuzzy Logic techniques.
OPTIM-AL has advanced in its knowledge by the application of computer aid tools to the
railway maintenance sector. Previous experience of this company was related to the building
and industrial sector. This project has increased the business opportunities for this
technology provider.
POLITO has advanced in its knowledge related to the evaluation of track condition by the
use of quality parameters. The gathered data during the measurement campaigns within this
project enabled further development in the evaluation and prediction algorithms.
1.4.5 Spin-off companies
The creation of spin-off companies has become an important mechanism to commercialise or
exploit research results, especially for the university. In this regard, one spin-off has already born
from the ACEM-Rail Project: Optosensing s.r.l. (www.optosensing.it) from Second University of
Naples (SUN), constituted on date 01/08/2013. Figure 40 shows the Optosensing logo.
Figure 40: Optosensing Logo
A future spin-off could be founded by another partner (Fraunhofer IZFP-D) for the commercial
exploitation of the hollow-shaft acoustic sensor.
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1.5 Consortium and Contact details
The composition of the consortium guarantees an optimal processing of the project targets. The
consortium is made up of the following organizations:
1. CEMOSA (Project Coordinator, Spain)
2. University of Seville (Scientific Manager, Spain)
3. Fraunhofer (Germany)
4. Politecnico di Torino (Italy)
5. Seconda Universita degli Studi di Napoli (Italy)
6. Optim-Al Ltd (Bulgaria)
7. DMA (Italy)
8. Tecnomatica (Italy)
9. SIEMENS (Germany)
10. ScanMaster Ltd. (Israel)
The contacts details can be addressed to www.acem-rail.eu and www.acem-rail.com
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2 Use and dissemination of foreground
Section A (public)
This section includes two tables:
Table A1: List of all scientific (peer reviewed) publications relating to the foreground of the
project.
Table A2: List of all dissemination activities (publications, conferences, workshops, web
sites/applications, press releases, flyers, articles published in the popular press, videos,
media briefings, presentations, exhibitions, thesis, interviews, films, TV clips, posters).
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TABLE A1: LIST OF SCIENTIFIC (PEER REVIEWED) PUBLICATIONS, STARTING WITH THE MOST IMPORTANT ONES
N. Title / DOI Author(s)
Title of the
periodical or the
series
Number, date
or frequency Publisher
Place of
publication
Date of
publication
Relevant
pages
Open
access ? Type
1
Differential pulse-width pair
BOTDA with fast fall-time
pulses
10.1109/ICSENS.2011.61271
87
Aldo Minardo,
Luigi Zeni ,
Romeo Bernini
2011 IEEE
SENSORS
Proceedings
IEEE 01/10/2011 897-900 No Conference
2
Long-range distributed
Brillouin fiber sensors by use
of an unbalanced double
sideband probe
10.1364/OE.19 .023845
Romeo Bernini,
Aldo Minardo,
Luigi Zeni
Optics Express Vol. 19/
Issue 24
Optical
Society of
America
United
States 09/11/2011
23845-
23856 Yes
Peer
reviewed
3
High-Spatial- and Spectral-
Resolution Ti me-Domain
Brillouin Distributed Sensing
by Use of Two Frequency-
Shifted Optical Beam Pairs
10.1109/JPHOT.2012.221930
1
A. Minardo, L.
Zeni , R.
Bernini
IEEE Photonics
Journal
Vol. 4/
Issue 5
Institute of
Electrical
and
Electronics
Engineers
Inc.
United
States 01/10/2012 1900-1908 Yes
Peer
reviewed
4
Distributed Sensing at
Centimeter-Scale Spatial
Resolution by BOFDA:
Measurements and Signal
Processing
10.1109/JPHOT.2011.217902
4
R. Bernini, A.
Minardo, L.
Zeni
IEEE Photonics
Journal Vol. 4/Issue 1
Institute of
Electrical
and
Electronics
Engineers
Inc.
United
States 01/02/2012 48-56 Yes
Peer
reviewed
5
Spatial Resolution
Enhancement in Preactivated
BOTDA Schemes by
Numerical Processing
10.1109/LPT.2 012.2192424
Aldo Minardo,
Romeo Bernini,
Luigi Zeni
IEEE Photonics
Technology
Letters
Vol. 24/
Issue 12
Institute of
Electrical
and
Electronics
Engineers
Inc.
United
States 01/06/2012 1003-1005 No
Peer
reviewed
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N. Title / DOI Author(s)
Title of the
periodical or the
series
Number, date
or frequency Publisher
Place of
publication
Date of
publication
Relevant
pages
Open
access ? Type
6
Differential Techniques for
High-Resolution BOTDA: An
Analytical Approach
10.1109/LPT.2 012.2202223
Aldo Minardo,
Romeo Bernini,
Luigi Zeni
IEEE Photonics
Technology
Letters
Vol. 24/
Issue 15
Institute of
Electrical
and
Electronics
Engineers
Inc.
United
States 01/08/2012 1295-1297 No
Peer
reviewed
7
Modal analysis of a cantilever
beam by use of Brillouin
based distributed dynamic
strain measurements
10.1088/0964-
1726/21/12/125022
Aldo Minardo,
Agnese
Coscetta ,
Salvato Pirozzi,
Romeo Bernini,
Luigi Zeni
Smart Materials
and Structures
Vol. 21/
Issue 12
Institute of
Physics
Publishing
United
Kingdom 01/12/2012 125022 No
Peer
reviewed
8
Real-time monitoring of
railway traffic using slope-
assisted Brillouin distributed
sensors
http://dx.doi.org/10.1364/AO.
52.003770
Aldo Minardo,
Giuseppe
Porcaro ,
Daniele
Giannetta ,
Romeo Bernini,
Luigi Zeni
Applied Optics Vol. 52/
Issue 16
Optical
Society of
America
United
States 01/01/2013 3770-3776 No
Peer
reviewed
9
The stochastic generalized bin
packing problem
http://dx.doi.org/10.1016/j.da
m.2011.1 0.037
Guido Perboli,
Roberto Tadei ,
Mauro M.
Baldi
Discrete Applied
Mathematics
Vol. 160/
Issue 7-8 Elsevier Netherlands 01/05/2012 1291-1297 No
Peer
reviewed
10
Job Order Assignment at
Optimal Costs in Railway
Maintenance
F. Heinicke , A.
Simroth, R.
Tadei, M. Baldi
Proceedings of the
2nd International
Conference on
Operations
Research and
Enterprise Systems
SciTePress 01/02/2013 304-309 No Conference
11
On a novel optimisation model
and solution method for
tactical railway maintenance
F. Heinicke, A.
Simroth, R.
Tadei
Proceedings of the
2nd International
Conference on
Department
of
Transportati
Zagreb,
Croatia 01/05/2012 421-427 Yes Conference
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N. Title / DOI Author(s)
Title of the
periodical or the
series
Number, date
or frequency Publisher
Place of
publication
Date of
publication
Relevant
pages
Open
access ? Type
planning Road and Rail
Infrastructure
on, Faculty
of Civil
Engineering,
University
of Zagreb
12 The Stochastic Generalized
Bin Packing Problem
G. Perboli, R.
Tadei, L.
Gobbato, M.
M. Baldi
Proceedings of the
XIII Int.
Conference on
Stochastic
Programming
Elsevier 09/07/2013 1291-1297 No Conference
13 A New Method to Evaluate
Track Conditions over Time
N. Bosso, A.
Gugliotta and
N. Zampieri
Proceedings of the
First International
Conference on
Railway
Technology:
Research,
Development and
Maintenance
Civil-Comp
Press
Stirlingshire
, UK 01/04/2012 Paper 47 No Conference
14
Asymptotic results for the
Generalized Bin Packing
Problem
M. M. Baldi, T.
G. Crainic, G.
Perboli, R.
Tadei
Proceedings of the
16th Euro
Working Group on
Transportation
Elsevier 04/09/2013 Yes Conference
15
Characterisation of Rail
Tracks by Means of Hollow
Shaft Integrated Acoustic
Sensor Systems
F. Schubert, M.
Barth, U.
Hoenig, H.
Neunuebel,
Mareike
Stephan, A.
Gommlich , L.
Schubert, B.
Frankenstein
Proceedings of the
European
Transport
Conference 2013
Association
for European
Transport
Frankfurt 01/10/2013 Yes Conference
16 A logical framework and F. Cores, N. Proceedings of the Association Frankfurt 01/10/2013 Yes Conference
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N. Title / DOI Author(s)
Title of the
periodical or the
series
Number, date
or frequency Publisher
Place of
publication
Date of
publication
Relevant
pages
Open
access ? Type
integrated architecture for the
rail maintenance automation
Caceres, F.G.
Benitez, S.
Escriba, N.
Jimenez-
Redondo
European
Transport
Conference 2013
for European
Transport
17
Automated and Cost Effective
Maintenance for Railway
(ACEM-Rail)
N. Jimenez-
Redondo, N.
Bosso, L. Zeni,
A. Minardo, F.
Schubert , F.
Heinicke , A.
Simroth
Proceedings
“Transport
Research Arena
2012”
Elsevier 24/04/2012 1058-1067 Yes Conference
18
Automatización y
optimización del
mantenimiento de la vía
(ACEM-Rail)
N. Jimenez-
Redondo, N.
Caceres, F. J.
Cores
Proceedings of the
10th Transport
Engineering
Conference
Editorial
Universidad
de Granada
01/06/2012 Paper 142 No Conference
19
Sistema inteligente de
automatización de la gestión
del mantenimiento de vía
N. Jimenez-
Redondo, P.
Cembrero , F.
Cores, F.G.
Benitez
Proceedings of the
7th Spanish
Conference on
Railway
Innovation
UNED Zaragoza 01/05/2012 547-560 No Conference
20 Generalized Bin Packing
Problems
Mauro Maria
Baldi
Politecnico
di Torino
Corso Duca
Degli
Abruzzi 24,
10129,
Torino,
Italy
28/02/2013 Yes Thesis
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TABLE A2: LIST ODF DISSEMINATION ACTIVITIES
No. Type of activities1 Main leader Title Date Place Type of audience
2 Countries addressed
1 oral presentation to a wider
public CEMOSA
6th Spanish Conference on Railway
Innovation 30/03/2011 Malaga, Spain
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers
National (Spain)
2 oral presentation to a
scientific event SCANMASTER
Annual convention of the Israeli
Branch of Non-Destructive testing 01/06/2011 Israel
Scientific community
(higher education,
Research)
Regional
3 Exhibitions SCANMASTER Defektoskopie 2011 07/09/2011 Ufa, Russia Industry International
4 Oral presentation to a
scientific event
SECONDA
UNIVERSITÀ
DEGLI STUDI
DI NAPOLI
IEEE Sensors 2011 28/10/2011 Limerick,
Ireland
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers
International
5 Oral presentation to a
scientific event
SECONDA
UNIVERSITÀ
DEGLI STUDI
DI NAPOLI
COST Action TD1001 - Novel and
Reliable Optical Fibre Sensor
Systems for Future Security and
Safety Applications (OFSESA)
01/11/2011 Jena, Germany
Scientific community
(higher education,
Research)
International
6 Exhibitions SCANMASTER
11 International Exhibition and
Conference for Non-Destructive
Testing and Technical Diagnostics
01/03/2012 Moscow, Russia
Scientific community
(higher education,
Research) - Industry
International
7 Exhibitions DMA EXPO Ferroviaria 2012 28/03/2012 Turin, Italy
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
International
1 Dissemination activity: publications, conferences, workshops, web, press releases, flyers, articles published in the popular press, videos, media briefings, presentations, exhibitions, thesis,
interviews, films, TV clips, posters, Other. 2 Type of public: Scientific Community (higher education, Research), Industry, Civil Society, Policy makers, Medias.
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No. Type of activities1 Main leader Title Date Place Type of audience
2 Countries addressed
makers - Medias
8 Oral presentation to a
scientific event
POLITECNICO
DI TORINO
The first International Conference
on Railway Technology: Research,
Development and Maintenance
20/04/2012
Las Palmas de
Gran Canarias,
Spain
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers - Medias
International
9 Organisation of Workshops OPTIM-AL
EOOD
Technical Meeting - Metropolitan
PLC (Metro Sofia) 17/04/2012 Sofia, Bulgaria
Industry - Policy
makers National (Bulgaria)
10 Oral presentation to a
scientific event CEMOSA
Transport Research Arena
(TRA2012) 24/04/2012 Athens, Greece.
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers - Medias
International
11 Oral presentation to a
scientific event FRAUNHOFER
2nd International Conference on
Road and Rail Infrastructure
(CETRA 2012)
07/05/2012 Dubrovnik,
Croacia
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers - Medias
International
12 Oral presentation to a
scientific event CEMOSA
7th Spanish Conference on Railway
Innovation (VII Congreso de
Innovación Ferroviaria)
10/05/2012 Zaragoza, Spain
Scientific community
(higher education,
Research) - Industry
National (Spain)
13 Oral presentation to a
scientific event
UNIVERSITY
OF SEVILLE
10th Transport Engineering
Conference (CIT2012) 21/06/2012 Granada, Spain
Industry - Civil society
- Policy makers -
Medias
National (Spain)
14 Organisation of Workshops Tecnomatica Seminar Infrastructure Maintenance
and ACEM-RAIL 29/11/2012 Sofia, Bulgaria
Scientific community
(higher education,
Research) - Industry
National (Bulgaria)
15 Oral presentation to a
scientific event FRAUNHOFER
2nd International Conference on
Operations Research and Enterprise
Systems (ICORES 2013)
16/02/2013 Barcelona,
Spain
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers - Medias
International
16 Oral presentation to a SECONDA 5th European Workshop on Optical 20/05/2013 Kraków, Poland Scientific community European
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No. Type of activities1 Main leader Title Date Place Type of audience
2 Countries addressed
scientific event UNIVERSITÀ
DEGLI STUDI
DI NAPOLI
Fiber Sensors (EWOFS'2013) (higher education,
Research)
17 Oral presentation to a
scientific event
POLITECNICO
DI TORINO
XIII International Conference on
Stochastic Programming
(ISCP2013)
09/07/2013 Bergamo, Italy
Scientific community
(higher education,
Research)
International
18 Oral presentation to a
scientific event FRAUNHOFER
The Third International Conference
on Soft Computing Technology in
Civil, Structural and Environmental
Engineering (CSC2013)
06/09/2013 Cagliari,
Sardinia, Italy
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers - Medias
International
19 Oral presentation to a
scientific event
POLITECNICO
DI TORINO
16th Euro Working Group on
Transportation (EWGT2013) 05/09/2013 Porto, Portugal
Scientific community
(higher education,
Research)
European
20 Oral presentation to a
scientific event
UNIVERSITY
OF SEVILLE
41st European Transport
Conference (ETC 2013) 01/10/2013
Frankfurt,
Germany
Scientific community
(higher education,
Research) - Industry -
Policy makers - Medias
European
21 Oral presentation to a
scientific event FRAUNHOFER
41st European Transport
Conference (ETC 2013) 01/10/2013
Frankfurt,
Germany
Scientific community
(higher education,
Research) - Industry -
Policy makers - Medias
European
22 Organisation of Workshops CEMOSA
FP7 Final Workshop: Towards a
More Efficient and Sustainable
Railway Maintenance
30/09/2013 Frankfurt,
Germany
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers - Medias
European
23 Press releases
SECONDA
UNIVERSITÀ
DEGLI STUDI
DI NAPOLI
Transporti Ferroviari, sensori hi-
tech per la sicurezza (newspapre Il
Mattino)
16/05/2011 Italy Civil society Regional
24 Exhibitions CEMOSA 9th World Congress on Railway
Research 23/05/2011 Lille, France
Scientific community
(higher education, International
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No. Type of activities1 Main leader Title Date Place Type of audience
2 Countries addressed
Research) - Industry -
Civil society - Policy
makers - Medias
25 Flyers CEMOSA First ACEM-Rail brochure 01/04/2012 Spain
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers - Medias
International
26 Flyers CEMOSA Final ACEM-Rail brochure 17/09/2013 Spain
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers - Medias
International
27 Posters DMA ACEM-Rail Poster for EXPO
Ferroviaria 2012 28/03/2012 Turin, Italy
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers - Medias
International
28 Posters UNIVERSITY
OF SEVILLE
ACEM-Rail Poster for Final
Workshop in ETC2013 30/09/2013
Frankfurt,
Germany
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers - Medias
European
29 Articles published in the
popular press CEMOSA
New in the local newspaper "Diario
Sur" 17/11/2011 Malaga, Spain Civil society Local
30 Press releases CEMOSA Article in EURAILmag Business &
Technology. Issue 27 01/04/2013 France
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers - Medias
European
31 Press releases CEMOSA Article in Spanish Railway -
Newsletter 10/2013 02/07/2013 Spain
Scientific community
(higher education,
Research) - Industry
International
EUROPEAN COMMISSION DG RTD
Final Publishable Report
© Copyright 2014, the members of the ACEM-Rail Page 56 of 57
No. Type of activities1 Main leader Title Date Place Type of audience
2 Countries addressed
32 Press releases CEMOSA New in Spanish Railway - Bulletin
of 17th July 2013 17/07/2013 Spain
Scientific community
(higher education,
Research) - Industry
National (Spain)
33 Articles published in the
popular press CEMOSA
Article in digital magazine
ASICMA. Issue 9 01/09/2012 Spain
Scientific community
(higher education,
Research) - Industry
National (Spain)
34 Press releases FRAUNHOFER Article in Fraunhofer IZFP Annual
Report 01/01/2012 Germany
Scientific community
(higher education,
Research) - Industry
National (Germany)
35 Press releases FRAUNHOFER Article in Fraunhofer IVI Annual
Report 01/01/2012 Germany
Scientific community
(higher education,
Research) - Industry
National (Germany)
36 Articles published in the
popular press
OPTIM-AL
EOOD
Article in digital newspaper
"TechNews Ltd" 15/03/2011 Bulgaria Civil society National (Bulgaria)
37 Articles published in the
popular press
OPTIM-AL
EOOD
Article in digital newspaper "Saga
Technology" 15/03/2011 Bulgaria Industry - Civil society National (Bulgaria)
38 Articles published in the
popular press
OPTIM-AL
EOOD
Article in digital newspaper "IDB
Bulgaria" 15/03/2011 Bulgaria Civil society National (Bulgaria)
39 Articles published in the
popular press
OPTIM-AL
EOOD
Article in digital magazine for
logistic "Logistika" 13/12/2012 Bulgaria Industry - Civil society National (Bulgaria)
40 Articles published in the
popular press
OPTIM-AL
EOOD
Article in digital magazine for
infrastructural construction
"STROITELI"
22/02/2013 Bulgaria
Scientific community
(higher education,
Research) - Industry -
Civil society
National (Bulgaria)
41 Articles published in the
popular press
OPTIM-AL
EOOD
Article in digital magazine "IT
Forum" 14/03/2011 Bulgaria Industry - Civil society National (Bulgaria)
42 Articles published in the
popular press
OPTIM-AL
EOOD
Article in digital newspaper
"Computerworld" 14/03/2011 Bulgaria Industry - Civil society National (Bulgaria)
43 Interviews OPTIM-AL
EOOD
Interview to three ACEM-Rail'
partners (CEMOSA, US and
OPTIM) and published in magazine
Logistika
12/12/2012 Bulgaria
Scientific community
(higher education,
Research) - Industry -
Civil society
National (Bulgaria)
44 Oral presentation to a wider Tecnomatica Oral presentation of the project 01/06/2012 Foggia, Italy Industry - Civil society National (Italy)
EUROPEAN COMMISSION DG RTD
Final Publishable Report
© Copyright 2014, the members of the ACEM-Rail Page 57 of 57
No. Type of activities1 Main leader Title Date Place Type of audience
2 Countries addressed
public during the presentation of the Rail
Tram by Gragano Railway line, in
Italy
- Policy makers -
Medias
45 Web sites/Applications CEMOSA ACEM-Rail fact sheet in ECOWEB 29/06/2013 Austria
Scientific community
(higher education,
Research) - Industry
European
46 Web sites/Applications CEMOSA ACEM-Rail project website 01/02/2011 Spain
Scientific community
(higher education,
Research) - Industry -
Civil society - Policy
makers - Medias
International
47 Press releases CEMOSA
Article in newsletter of
TECNIBERIA (Spanish
Association of Engineering,
Consulting and Technical Services)
24/02/2012 Spain
Scientific community
(higher education,
Research) - Industry
National (Spain)
48 Press releases CEMOSA New in SOST (Spanish Office for
Science and Technology) website 14/02/2011 Brussels
Scientific community
(higher education,
Research) - Industry
European
49 Oral presentation to a wider
public CEMOSA
Presentation in Regional Info-day
on Transport 29/05/2012 Seville, Spain
Scientific community
(higher education,
Research) - Industry
National (Spain)